MapReduce-Based Pattern Finding Algorithm Applied in Motif Detection for Prescription Compatibility Network

  • Yang Liu
  • Xiaohong Jiang
  • Huajun Chen
  • Jun Ma
  • Xiangyu Zhang
Conference paper

DOI: 10.1007/978-3-642-03644-6_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5737)
Cite this paper as:
Liu Y., Jiang X., Chen H., Ma J., Zhang X. (2009) MapReduce-Based Pattern Finding Algorithm Applied in Motif Detection for Prescription Compatibility Network. In: Dou Y., Gruber R., Joller J.M. (eds) Advanced Parallel Processing Technologies. APPT 2009. Lecture Notes in Computer Science, vol 5737. Springer, Berlin, Heidelberg

Abstract

Network motifs are basic building blocks in complex networks. Motif detection has recently attracted much attention as a topic to uncover structural design principles of complex networks. Pattern finding is the most computationally expensive step in the process of motif detection. In this paper, we design a pattern finding algorithm based on Google MapReduce to improve the efficiency. Performance evaluation shows our algorithm can facilitates the detection of larger motifs in large size networks and has good scalability. We apply it in the prescription network and find some commonly used prescription network motifs that provide the possibility to further discover the law of prescription compatibility.

Keywords

complex network motif detection pattern finding MapReduce prescription compatibility 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yang Liu
    • 1
  • Xiaohong Jiang
    • 1
  • Huajun Chen
    • 1
  • Jun Ma
    • 1
  • Xiangyu Zhang
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhouChina

Personalised recommendations